91 citations · 296 across the 23 of their papers we have counts for
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DCNNs on a Diet: Sampling Strategies for Reducing the Training Set Size
Maya Kabkab, Azadeh Alavi, Rama Chellappa
Large-scale supervised classification algorithms, especially those based on deep convolutional neural networks (DCNNs), require vast amounts of training data to achieve state-of-th…
Attributes for Improved Attributes: A Multi-Task Network for Attribute Classification
Emily M. Hand, Rama Chellappa
Attributes, or semantic features, have gained popularity in the past few years in domains ranging from activity recognition in video to face verification. Improving the accuracy of…
Convolutional Neural Networks for Attribute-based Active Authentication on Mobile Devices
Pouya Samangouei, Rama Chellappa
We present a Deep Convolutional Neural Network (DCNN) architecture for the task of continuous authentication on mobile devices. To deal with the limited resources of these devices,…
Optimized Kernel-based Projection Space of Riemannian Manifolds
Azadeh Alavi, Vishal M Patel, Rama Chellappa
It is proven that encoding images and videos through Symmetric Positive Definite (SPD) matrices, and considering the Riemannian geometry of the resulting space, can lead to increas…
Triplet Similarity Embedding for Face Verification
Swami Sankaranarayanan, Azadeh Alavi, Rama Chellappa
In this work, we present an unconstrained face verification algorithm and evaluate it on the recently released IJB-A dataset that aims to push the boundaries of face verification m…
Deep Feature-based Face Detection on Mobile Devices
Sayantan Sarkar, Vishal M. Patel, Rama Chellappa
We propose a deep feature-based face detector for mobile devices to detect user's face acquired by the front facing camera. The proposed method is able to detect faces in images co…